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Forecasting Chinese Stock Market Volatility With Intraday and Overnight Volatility Components of INE Oil Futures

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Listed:
  • Qihao Chen
  • Zhuo Huang

Abstract

This paper investigates the role of different volatility components of the Shanghai International Energy Exchange (INE) oil futures, including intraday, overnight, and the first half‐hour components, in forecasting Chinese stock market volatility. Using 5‐min realized volatility (RV) as realized volatility measure (RM), the log‐HAR models are applied to generate one‐step‐ahead forecasts for three Chinese stock indices (CSI 300, SHSE and SZSE). Our out‐of‐sample results show that the model extended with 5‐min RV of INE oil futures does not generate more accurate volatility forecasts than the baseline log‐HAR model. However, the overnight volatility of INE oil futures significantly improves forecasting accuracy. Our results are robust across different estimation schemes, estimation windows, out‐of‐sample periods, and evaluation methods. Additionally, using Bi‐Power Variation (BPV) as an alternative RM yields consistent results. Overall, the results highlight the importance of incorporating the overnight volatility component of INE oil futures in forecasting Chinese stock market volatility.

Suggested Citation

  • Qihao Chen & Zhuo Huang, 2025. "Forecasting Chinese Stock Market Volatility With Intraday and Overnight Volatility Components of INE Oil Futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 45(10), pages 1665-1682, October.
  • Handle: RePEc:wly:jfutmk:v:45:y:2025:i:10:p:1665-1682
    DOI: 10.1002/fut.70008
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    References listed on IDEAS

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    1. Hamilton, James D., 1996. "This is what happened to the oil price-macroeconomy relationship," Journal of Monetary Economics, Elsevier, vol. 38(2), pages 215-220, October.
    2. Lutz Kilian & Clara Vega, 2011. "Do Energy Prices Respond to U.S. Macroeconomic News? A Test of the Hypothesis of Predetermined Energy Prices," The Review of Economics and Statistics, MIT Press, vol. 93(2), pages 660-671, May.
    3. Gisser, Micha & Goodwin, Thomas H, 1986. "Crude Oil and the Macroeconomy: Tests of Some Popular Notions: A Note," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 18(1), pages 95-103, February.
    4. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    5. Lutz Kilian, 2009. "Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market," American Economic Review, American Economic Association, vol. 99(3), pages 1053-1069, June.
    6. Hamilton, James D., 2003. "What is an oil shock?," Journal of Econometrics, Elsevier, vol. 113(2), pages 363-398, April.
    7. repec:aen:journl:1995v16-04-a02 is not listed on IDEAS
    8. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    9. Wang, Jiqian & Huang, Yisu & Ma, Feng & Chevallier, Julien, 2020. "Does high-frequency crude oil futures data contain useful information for predicting volatility in the US stock market? New evidence," Energy Economics, Elsevier, vol. 91(C).
    10. Todd E. Clark & Michael W. McCracken, 2009. "Improving Forecast Accuracy By Combining Recursive And Rolling Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 50(2), pages 363-395, May.
    11. John Y. Campbell & Samuel B. Thompson, 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
    12. Robert C Ready, 2018. "Oil Prices and the Stock Market [The vix, the variance premium and stock market volatility]," Review of Finance, European Finance Association, vol. 22(1), pages 155-176.
    13. Hamilton, James D, 1983. "Oil and the Macroeconomy since World War II," Journal of Political Economy, University of Chicago Press, vol. 91(2), pages 228-248, April.
    14. Maria Ghani & Feng Ma & Dengshi Huang, 2024. "Forecasting the Asian stock market volatility: Evidence from WTI and INE oil futures," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 1496-1512, April.
    15. Lutz Kilian, 2008. "Exogenous Oil Supply Shocks: How Big Are They and How Much Do They Matter for the U.S. Economy?," The Review of Economics and Statistics, MIT Press, vol. 90(2), pages 216-240, May.
    16. Kiseok Lee & Shawn Ni & Ronald A. Ratti, 1995. "Oil Shocks and the Macroeconomy: The Role of Price Variability," The Energy Journal, , vol. 16(4), pages 39-56, October.
    17. Taylor, Nick, 2017. "Realised variance forecasting under Box-Cox transformations," International Journal of Forecasting, Elsevier, vol. 33(4), pages 770-785.
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